Optimization based control for target estimation and tracking via highly observable trajectories

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Linear-Quadratic-Gaussian (LQG) control is a fundamental control paradigm that is studied in various fields such as engineering, computer science, economics, and neuroscience. It involves controlling a system with linear dynamics and imperfect observations ...

For people with limited mobility, navigating in cluttered indoor environment is challenging. In this work, we propose a mobile assistive furniture suite that is designed to ease the life of people with special needs in indoor movement. To enable intelligen ...

We present a robust model predictive control (MPC) framework for linear systems facing bounded parametric uncertainty and bounded disturbances. Our approach deviates from standard MPC formulations by integrating multi-step predictors, which provide reduced ...

Daily manipulation tasks are characterized by regular features associated with the task structure, which can be described by multiple geometric primitives related to actions and object shapes. Only using Cartesian coordinate systems cannot fully represent ...

This thesis is situated at the crossroads between machine learning and control engineering. Our contributions are both theoretical, through proposing a new uncertainty quantification methodology in a kernelized context; and experimental, through investigat ...

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

Over the past two decades, the thermo-hydro-mechanical behavior of earth-contact structures such as piles, walls, slabs, and tunnels, which simultaneously provide structural support and energy supply, has been studied through various field experiments and ...

The paper considers the problem of estimating the parameters of the compound admittance matrix of three-phase untransposed low-and medium-voltage electrical distribution networks using synchrophasor measurements from phasor measurement units (PMUs). The wo ...

Optimization based control for target estimation and tracking via highly observable trajectories

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Distributionally Robust Linear Quadratic Control

Real-Time Localization for Closed-Loop Control of Assistive Furniture

Homothetic Tube Model Predictive Control With Multi-Step Predictors

A geometric optimal control approach for imitation and generalization of manipulation skills

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

An equilibrated flux a posteriori error estimator for defeaturing problems

Learning and optimization of anticipatory feedback controllers for robot manipulation

Thermo-hydro-mechanical behavior of energy barrettes: Field experiments and numerical simulations

Compound Admittance Matrix Estimation of Three-phase Untransposed Power Distribution Grids using Synchrophasor Measurements